title: Effective cluster-based seed design for cross-species sequence comparisons.
abstract: CONCLUSIONS
  To annotate newly sequenced organisms, cross-species sequence comparison algorithms can be applied to align gene sequences to the genome of a related species. To improve the accuracy of alignment, spaced seeds must be optimized for each comparison. As the number and diversity of genomes increase, an efficient alternative is to cluster pairwise comparisons into groups and identify seeds for groups instead of individual comparisons. Here we investigate a measure of comparison closeness and identify classes of comparisons that show similar seed behavior and therefore can employ the same seed.
  
  
  BACKGROUND
  Source code is freely available at http://dna.cs.gwu.edu and from Bioinformatics online.
authors.affiliation: Department of Computer Science, George Washington University, Washington, DC 20052, USA. lmzhou@gwmail.gwu.edu
authors.forename: Leming
authors.initials: L
authors.lastname: Zhou
authors.forename: Ingrid
authors.initials: I
authors.lastname: Mihai
authors.forename: Liliana
authors.initials: L
authors.lastname: Florea
mesh_terms: D000465:Algorithms; D000818:Animals; D001483:Base Sequence; D016000:Cluster Analysis; D016678:Genome; D006801:Humans; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods